System and method for automatically providing alternative points of view for multimedia content

ABSTRACT

A selection of content from a content presentation is received. At least one topic from the selected content is extracted using natural language processing (NLP). The at least one topic is representative of a subject conveyed within the selected content. At least one perspective associated with the at least one topic is extracted using NLP. The at least one perspective is representative of a point of view conveyed within the selected content regarding the at least one topic. A topic rating of the extracted topics and associated perspectives is determined based upon the extracted topics and associated perspectives. The topic rating is representative of a topic diversity among the extracted topics and associated perspectives. The topic rating is presented within a graphical user interface (GUI).

TECHNICAL FIELD

The present invention relates generally to a method, system, andcomputer program product for providing multimedia content. Moreparticularly, the present invention relates to a method, system, andcomputer program product for automatically providing alternative pointsof view for multimedia content.

BACKGROUND

The consumption of media such as social media continues to increase atan accelerating rate. Users often wish to engage with media on topicsthat contain a fair and balanced treatment of a subject, or that, atleast, present differing points of view (perspectives) on a subject. Forexample, a user may wish to be pointed to content (e.g., essays) thatgive various “sides” of an issue rather than a single perspective, forexample a conservative viewpoint versus a liberal viewpoint on aparticular subject. Social media sites visited by users often attempt toprovide media consistent with particular perceived ideologies andinterests. As a result, ideological and interest-based “echo chambers”have been created for users in which a particular user encounters onlybeliefs or opinions that coincide with the user's own, so that theuser's existing views are reinforced, and alternative ideas are notconsidered. These echo chambers extend beyond politics to science,social science, and also the arts. However, many users would like toescape their echo-chambers and receive a more balanced set ofperspectives on different issues and subject matters.

SUMMARY

The illustrative embodiments provide a method, system, and computerprogram product. An embodiment of a method includes receiving aselection of content from a content presentation. The embodiment furtherincludes extracting, using natural language processing (NLP), at leastone topic from the selected content. In the embodiment, the at least onetopic is representative of a subject conveyed within the selectedcontent. The embodiment further includes extracting, using NLP, at leastone perspective associated with the at least one topic. In theembodiment, the at least one perspective is representative of a point ofview conveyed within the selected content regarding the at least onetopic. The embodiment further includes determining a topic rating of theextracted topics and associated perspectives based upon the extractedtopics and associated perspectives. In the embodiment, the topic ratingis representative of a topic diversity among the extracted topics andassociated perspectives. The embodiment further includes presenting thetopic rating within a graphical user interface (GUI).

Another embodiment further includes searching a content source forcomplementary content based upon the topic rating to determine one ormore complementary content search results for the extracted topics andperspectives, and receiving a selection from among the one or morecomplementary content search results. Another embodiment furtherincludes presenting the one or more complementary content search resultsin the GUI, and receiving the selection from among the one or morecomplementary content search results using the GUI.

Another embodiment further includes retrieving complementary contentassociated with the selected complementary content search results, andproviding the complementary content within the GUI. In anotherembodiment, the complementary content is presented within the GUI aspart of a Web browser plugin. In another embodiment, the complementarycontent is presented within a pop up window in the GUI. In anotherembodiment, the complementary content is presented within the GUI aspart of an electronic book. In another embodiment, the complementarycontent is presented within a broadcast. In another embodiment, thecomplementary content is presented as closed caption information withinthe broadcast.

In another embodiment, extracting the at least one topic includesrepresenting the at least one topic as a vector in a vector space. Inanother embodiment, the extracting of the at least one topic includesusing one or more of probabilistic latent semantic indexing (PLSI),Latent Dirichlet allocation (LDA), Pachinko allocation, singular valuedecomposition (SVD), the method of moments, and non-negative matrixfactorization (NMF).

In another embodiment, the topic rating is representative of one of anorthogonality, an opposition, and an independence among the extractedtopics and associated perspectives. In another embodiment, the GUI isconfigured to allow a user to select the content from the contentpresentation. In another embodiment, the extracting of the topic isperformed at one or more of a sentence level of content organization anda document level of content organization.

In another embodiment, the GUI includes an electronic calendarapplication having at least one calendar entry, the GUI allowingselection of the at least one calendar entry, and wherein thecomplementary content includes at least one of an alternative point ofview of a meeting topic associated with the calendar entry, a link toone or more other calendar entries providing a complementary viewpoint.In another embodiment, the other calendar entries are sorted in order ofdegree of complementarity.

An embodiment includes a computer usable program product. The computerusable program product includes one or more computer-readable storagedevices, and program instructions stored on at least one of the one ormore storage devices.

An embodiment includes a computer system. The computer system includesone or more processors, one or more computer-readable memories, and oneor more computer-readable storage devices, and program instructionsstored on at least one of the one or more storage devices for executionby at least one of the one or more processors via at least one of theone or more memories.

BRIEF DESCRIPTION OF THE DRAWINGS

Certain novel features believed characteristic of the invention are setforth in the appended claims. The invention itself, however, as well asa preferred mode of use, further objectives and advantages thereof, willbest be understood by reference to the following detailed description ofthe illustrative embodiments when read in conjunction with theaccompanying drawings, wherein:

FIG. 1 depicts a block diagram of a network of data processing systemsin which illustrative embodiments may be implemented;

FIG. 2 depicts a block diagram of a data processing system in whichillustrative embodiments may be implemented;

FIG. 3 depicts a block diagram of an example configuration for providingcomplementary media content for selected media content in accordancewith an illustrative embodiment;

FIGS. 4A-4B depict an example of a web browser based GUI in accordancewith an illustrative embodiment;

FIG. 5 depicts an example of a calendar application based GUI inaccordance with an illustrative embodiment; and

FIG. 6 depicts a flowchart of an example process for providingcomplementary media content for selected media content in accordancewith an illustrative embodiment.

DETAILED DESCRIPTION

The illustrative embodiments recognize that the presently availabletools or solutions do not address these needs or provide adequatesolutions for these needs. The illustrative embodiments used to describethe invention generally address and solve the above-described problemsand other problems related to providing complementary media contentincluding alternative points of view for selected media content.

An embodiment can be implemented as a software application. Theapplication implementing an embodiment can be configured as amodification of an existing media content provider system, as a separateapplication that operates in conjunction with an existing media contentprovider system, a standalone application, or some combination thereof.

One or more embodiments are directed to a method and system forpresenting multimedia content to a user, detecting and/or extractingtopics and points of view (perspectives) in the content, and a providinga rating of topic diversity, for example “orthogonality”, independence,or opposition, determined based upon the perspectives to a user. Inparticular embodiments, the multimedia content may include, for example,text within a Web browser, an essay, a book, an electronic book (eBook),broadcast media such as a television program, vocal output of broadcastcommentators, a news story, a blog post, a PowerPoint presentation, amagazine article, or a technical journal papers. In one or moreembodiments, the rating of topic diversity is used to search forcomplementary content and automatically provide access to thecomplementary content to the user.

As background, note that “a point of view” is a specified or statedmanner of consideration, an attitude regarding how one sees or thinks ofsomething, as in “from doctor's point of view”. In this meaning, theusage of “point of view” is synonymous with one of the meanings of theterm perspective. In machine learning and natural language processing(NLP), a topic model is a type of statistical model for discoveringabstract “topics” that occur in a collection of documents in which atopic represents a subject or theme conveyed within content.

Users often wish to engage in topics that contain a fair and balancedtreatment of a subject, or at least differing points of views(perspectives) on a subject. For example, a user may wish to be pointedto content (e.g. essays) that provide various “sides” of an issue ratherthan a single perspective such as solely a conservative or liberalviewpoint on a subject. Providing differing perspectives on a topic isnot only useful in the field of education, but people reading orlistening to news stories may also welcome this feature forautomatically obtaining varied points of view about a particular topicso that a diversity of perspectives regarding a particular topic can bemade available to a user.

In one or more embodiments, a perspective associated with a topic ismathematically represented as a vector in a vector space. In vectorspaces, diversity can be measured by comparing vectors to each other orby deriving a statistic for an ensemble of vectors. For example, twovectors may be determined to be orthogonal (90 degrees apart) from oneanother or opposite (180 degrees apart) from one another with respect toa perspective represented by the individual vectors. Ensembles ofvectors may be diverse and contain vectors that cover a vector space. Inan ensemble of vectors, a useful measure of diversity is a particularvector's statistical independence from the ensemble. Vectors thatmaximize their independence from the ensemble also maximize the entropyof the ensemble. When the ensemble is a function of some other ensemble,the maximally independent vectors maximize the information about theother ensemble.

In particular embodiments, a system performs topic extraction onmultimedia content using one or more of probabilistic latent semanticindexing (PLSI), Latent Dirichlet allocation (LDA), Pachinko allocation,singular value decomposition (SVD), the method of moments, algorithmsbased upon non-negative matrix factorization (NMF), or any othersuitable algorithm or procedure for extracting topics from multimediacontent.

In an embodiment, extracting a topic from multimedia content includesrepresenting the multimedia content as a vector in a vector space. Inthe embodiment, a system or application system compares topic vectors toeach other or to an ensemble of topic vectors. In particularembodiments, an application accesses software and/or librariesconfigured for topic extraction to facilitate the extraction of topicsand perspectives from multimedia content.

In one or more embodiments, the application receives a selection ofmultimedia content from a user, extracts one or more topics andcorresponding perspectives from the selected content, determines a topicrating for an extracted topic, searches one or more complementarycontent sources for complementary content based upon the topic rating,and presents a listing of one or more choices of complementary content(e.g., an alternate point of view) as a suggestion to a consumer (e.g.,a user) of the multimedia content within a graphical user interface(GUI) of a client device. In an embodiment, the graphical user interfacefurther includes an indication of the whether the complementary contentis orthogonal, opposite, or maximally independent from a given topic orensemble of topics. In particular embodiments, complementary content(e.g. an alternate point of view) may be suggested to a consumer ofcontent as part of an eBook or as part a broadcast television feature.

In an embodiment, a GUI is provided to allow a user to select sectionsof a document (e.g. containing assertions) to provide an alternate pointof view to the selected content. In a particular embodiment, colors ofthe GUI buttons may indicate degree of complementarity (ororthogonality) of the respective viewpoint of the complementary content.In another particular embodiment, a user selects a GUI button in a Webbrowser interface to find and be presented with an alternate point ofview for the currently displayed content.

Various embodiments may be directed to different levels of contentorganization. In one example, a system or application operates at adocument level in which a perspective from which a document is writtenor a video is produced is identified from the content. In anotherexample, the system or application operates at a sentence level in whichsentences are identified that strongly express a particular perspectivein order to offer a diversity of perspectives.

In a particular usage example, the system or application may employ amachine learning model to identify thesis statements in student essaysas a classification task and then present complementary viewpoints tothe statements. In another particular usage example, the system orapplication may be used by authors of newspaper articles or students toaid in end-to-end argument mining in persuasive essays. In anotherparticular usage example, the system or application may be used to findother social networks or bulletin boards that express complementarypoints of view. In another particular usage example, the system orapplication may be used by reviewers of content in magazines, technicaljournals, etc. In another particular usage example, the system orapplication may be used by debaters, lawmakers, policy makers,politicians, etc. to present alternative viewpoints from theircompetition.

In one or more embodiments, various visualization choices may be offeredas indicators to the diversity of views presented in content, e.g., anarticle, to the user such as a particular color in text, in a table ofcontents, etc. In particular embodiments, a GUI may be used to pop updifferent windows and present display screens (or Web browser windows)showing complementary content. In another particular embodiment, colorsof the GUI buttons may indicate degree of complementarity (ororthogonality) of viewpoint.

In another embodiment, the system or application interfaces with acalendar application to enable a GUI to provide a user withcomplementary content related to a meeting scheduled in the calendarapplication in response to a selection by the user. In a particularembodiment, the GUI includes a button associated with one or morecalendar entries to allow a user to select the button to obtainalternative points of view on a meeting topic associated with theparticular meeting corresponding to the calendar entry. For example, auser preparing for a meeting on the topic of the future of blockchainapplications may press the button and become better prepared by beingprovided with complementary content for the topic including alternativepoints of view (e.g. links to presentations, web pages, articles, etc.).In other particular embodiments, the buttons may also be pressed after ameeting to learn more about a meeting topic of a past meeting. Inparticular embodiments, input to the system or application may includecalendar information for a meeting, an attendee list (and job titles andorganizations for which the attendees work), and any attachedpresentations or links to content associated with a meeting, etc.Calendar entries may include entries for meetings, announcements,presentations on topics, etc. Such GUI buttons on calendars may alsoprovide links to other meetings (past or future) that provide similar orcomplementary viewpoints. Viewpoints may initially only be estimatesbased on sparse information, but such information may be updated asmeeting information is attached or linked to a calendar entry. Moreover,such GUI buttons on calendars can be used to “show me all meetings” withcomplementary viewpoints sorted in order of degree of complementarity.

In a Web-based eCommerce usage example, a user may shop for particularcontent, such as a book or article, on an eCommerce website and beprovided with a listing of articles or books with alternative orcomplementary viewpoints for purchase. In a particular embodiment, GUIbuttons may be presented at such eCommerce websites for selecting topurchase the “orthogonal” content items for sale.

In another embodiment, a service is implemented to maintain a largemulti-dimensional array of topics, and one or more GUI buttons asdescribed above as based, in part, upon lookups into the array. By wayof example, consider an article A about the Spanish exploring SouthAmerica, and then declaring, “This land belongs to the Spanish Empire!”The Spanish thought the Spanish culture was superior to the indigenousculture. Using a look-up table, an “Alternative perspective” includesone or more articles B on Peru from the point of view of the Incans,describing advanced civilizations, governments, and religions, etc. Inanother example, candidate articles for B may have certain topics, whichare determined from latent semantic indexing and the like. In theembodiment, rules are implemented in the form of: if article A hastopics 1, 2, and 3, then it return articles B with topics 4, 5, and 6.

In another embodiment, author diversity is used to determinecomplementary media content. In particular embodiments, GUI buttons mayalso take into consideration the author of an article, or host of ashow, etc., when known. In such a case, difference of view point mightbe partially estimated by authorship. For example, if a user is readinga writing by author Noam Chomsky and presses the GUI button, the usermay be provided with a writing by Sam Harris on the same topic.

In another embodiment, the determination of complementary media contentis performed in association with a closed captioning application. In anexample application, a user is watching the evening news on apolitically conservative TV channel, and alternative viewpoints arepresented as closed caption information in text on the bottom of thescreen.

In yet another embodiment, the GUI is used to highlight the topicswithin a document for which a viewpoint (e.g. conservative or liberal)can be ascertained. In an example usage, a service can be provided toassist students in interpreting an essay or text book.

In still another embodiment, topics are compared to an ensemble of giventopics using procedures such as Principal Component Analysis, SingularValue Decomposition (SVD), or Independent Component Analysis (ICA).

In another embodiment, the complementary content (e.g. alternate pointof view) is suggested or presented to a consumer of the content as parta Web browser plugin. In one or more embodiments, the complementarycontent is one of orthogonal to, opposite of, independent from theselected media content. In another embodiment, the complementary contentis suggested or presented to a consumer of the selected content as partof an eBook. In still another embodiment, the complementary content issuggested or presented to a consumer of the selected content as part abroadcast (e.g., television) feature.

In another embodiment, a GUI is used to select sections of a document(e.g., sentences containing assertions) to provide an alternate point ofview of the selected sections.

In various embodiments, the extracting of topics is performed at asentence level, a document level, or any other level of contentorganization. In another embodiment, the system or application pops upwindows showing the complementary content that is different from awindow showing the selected content.

The manner of providing complementary media content for selected mediacontent is unavailable in the presently available methods. A method ofan embodiment described herein, when implemented to execute on a deviceor data processing system, comprises substantial advancement of thefunctionality of that device or data processing system in providingcomplementary media content for selected media content.

The illustrative embodiments are described with respect to certain typesof content, content sources, transmissions, topics, ratings, topic andperspective extraction procedures and algorithms, GUIs, devices, dataprocessing systems, environments, components, and applications only asexamples. Any specific manifestations of these and other similarartifacts are not intended to be limiting to the invention. Any suitablemanifestation of these and other similar artifacts can be selectedwithin the scope of the illustrative embodiments.

Furthermore, the illustrative embodiments may be implemented withrespect to any type of data, data source, or access to a data sourceover a data network. Any type of data storage device may provide thedata to an embodiment of the invention, either locally at a dataprocessing system or over a data network, within the scope of theinvention. Where an embodiment is described using a mobile device, anytype of data storage device suitable for use with the mobile device mayprovide the data to such embodiment, either locally at the mobile deviceor over a data network, within the scope of the illustrativeembodiments.

The illustrative embodiments are described using specific code, designs,architectures, protocols, layouts, schematics, and tools only asexamples and are not limiting to the illustrative embodiments.Furthermore, the illustrative embodiments are described in someinstances using particular software, tools, and data processingenvironments only as an example for the clarity of the description. Theillustrative embodiments may be used in conjunction with othercomparable or similarly purposed structures, systems, applications, orarchitectures. For example, other comparable mobile devices, structures,systems, applications, or architectures therefor, may be used inconjunction with such embodiment of the invention within the scope ofthe invention. An illustrative embodiment may be implemented inhardware, software, or a combination thereof.

The examples in this disclosure are used only for the clarity of thedescription and are not limiting to the illustrative embodiments.Additional data, operations, actions, tasks, activities, andmanipulations will be conceivable from this disclosure and the same arecontemplated within the scope of the illustrative embodiments.

Any advantages listed herein are only examples and are not intended tobe limiting to the illustrative embodiments. Additional or differentadvantages may be realized by specific illustrative embodiments.Furthermore, a particular illustrative embodiment may have some, all, ornone of the advantages listed above.

With reference to the figures and in particular with reference to FIGS.1 and 2, these figures are example diagrams of data processingenvironments in which illustrative embodiments may be implemented. FIGS.1 and 2 are only examples and are not intended to assert or imply anylimitation with regard to the environments in which differentembodiments may be implemented. A particular implementation may makemany modifications to the depicted environments based on the followingdescription.

FIG. 1 depicts a block diagram of a network of data processing systemsin which illustrative embodiments may be implemented. Data processingenvironment 100 is a network of computers in which the illustrativeembodiments may be implemented. Data processing environment 100 includesnetwork 102. Network 102 is the medium used to provide communicationslinks between various devices and computers connected together withindata processing environment 100. Network 102 may include connections,such as wire, wireless communication links, or fiber optic cables.

Clients or servers are only example roles of certain data processingsystems connected to network 102 and are not intended to exclude otherconfigurations or roles for these data processing systems. Server 104and server 106 couple to network 102 along with storage unit 108.Software applications may execute on any computer in data processingenvironment 100. Clients 110, 112, and 114 are also coupled to network102. A data processing system, such as server 104 or 106, or client 110,112, or 114 may contain data and may have software applications orsoftware tools executing thereon.

Only as an example, and without implying any limitation to sucharchitecture, FIG. 1 depicts certain components that are usable in anexample implementation of an embodiment. For example, servers 104 and106, and clients 110, 112, 114, are depicted as servers and clients onlyas example and not to imply a limitation to a client-serverarchitecture. As another example, an embodiment can be distributedacross several data processing systems and a data network as shown,whereas another embodiment can be implemented on a single dataprocessing system within the scope of the illustrative embodiments. Dataprocessing systems 104, 106, 110, 112, and 114 also represent examplenodes in a cluster, partitions, and other configurations suitable forimplementing an embodiment.

Device 132 is an example of a device described herein. For example,device 132 can take the form of a smartphone, a tablet computer, alaptop computer, client 110 in a stationary or a portable form, awearable computing device, or any other suitable device. Any softwareapplication described as executing in another data processing system inFIG. 1 can be configured to execute in device 132 in a similar manner.Any data or information stored or produced in another data processingsystem in FIG. 1 can be configured to be stored or produced in device132 in a similar manner.

Application 105 implements an embodiment described herein. Server 106includes a natural language processing engine (NLP) 107 configured toprocess media content and perform natural language processing on themedia content to extract topics and perspectives from the media content.In other embodiments, application 105 may be configured to perform theextracting of topics and perspectives from media content. Multimediacontent 109, such as complementary media content, may be stored instorage 108 as shown or supplied by another source (not shown).

Servers 104 and 106, storage unit 108, and clients 110, 112, and 114,and device 132 may couple to network 102 using wired connections,wireless communication protocols, or other suitable data connectivity.Clients 110, 112, and 114 may be, for example, personal computers ornetwork computers.

In the depicted example, server 104 may provide data, such as bootfiles, operating system images, and applications to clients 110, 112,and 114. Clients 110, 112, and 114 may be clients to server 104 in thisexample. Clients 110, 112, 114, or some combination thereof, may includetheir own data, boot files, operating system images, and applications.Data processing environment 100 may include additional servers, clients,and other devices that are not shown.

In the depicted example, data processing environment 100 may be theInternet. Network 102 may represent a collection of networks andgateways that use the Transmission Control Protocol/Internet Protocol(TCP/IP) and other protocols to communicate with one another. At theheart of the Internet is a backbone of data communication links betweenmajor nodes or host computers, including thousands of commercial,governmental, educational, and other computer systems that route dataand messages. Of course, data processing environment 100 also may beimplemented as a number of different types of networks, such as forexample, an intranet, a local area network (LAN), or a wide area network(WAN). FIG. 1 is intended as an example, and not as an architecturallimitation for the different illustrative embodiments.

Among other uses, data processing environment 100 may be used forimplementing a client-server environment in which the illustrativeembodiments may be implemented. A client-server environment enablessoftware applications and data to be distributed across a network suchthat an application functions by using the interactivity between aclient data processing system and a server data processing system. Dataprocessing environment 100 may also employ a service orientedarchitecture where interoperable software components distributed acrossa network may be packaged together as coherent business applications.Data processing environment 100 may also take the form of a cloud, andemploy a cloud computing model of service delivery for enablingconvenient, on-demand network access to a shared pool of configurablecomputing resources (e.g. networks, network bandwidth, servers,processing, memory, storage, applications, virtual machines, andservices) that can be rapidly provisioned and released with minimalmanagement effort or interaction with a provider of the service.

With reference to FIG. 2, this figure depicts a block diagram of a dataprocessing system in which illustrative embodiments may be implemented.Data processing system 200 is an example of a computer, such as servers104 and 106, or clients 110, 112, and 114 in FIG. 1, or another type ofdevice in which computer usable program code or instructionsimplementing the processes may be located for the illustrativeembodiments.

Data processing system 200 is also representative of a data processingsystem or a configuration therein, such as data processing system 132 inFIG. 1 in which computer usable program code or instructionsimplementing the processes of the illustrative embodiments may belocated. Data processing system 200 is described as a computer only asan example, without being limited thereto. Implementations in the formof other devices, such as device 132 in FIG. 1, may modify dataprocessing system 200, such as by adding a touch interface, and eveneliminate certain depicted components from data processing system 200without departing from the general description of the operations andfunctions of data processing system 200 described herein.

In the depicted example, data processing system 200 employs a hubarchitecture including North Bridge and memory controller hub (NB/MCH)202 and South Bridge and input/output (I/O) controller hub (SB/ICH) 204.Processing unit 206, main memory 208, and graphics processor 210 arecoupled to North Bridge and memory controller hub (NB/MCH) 202.Processing unit 206 may contain one or more processors and may beimplemented using one or more heterogeneous processor systems.Processing unit 206 may be a multi-core processor. Graphics processor210 may be coupled to NB/MCH 202 through an accelerated graphics port(AGP) in certain implementations.

In the depicted example, local area network (LAN) adapter 212 is coupledto South Bridge and I/O controller hub (SB/ICH) 204. Audio adapter 216,keyboard and mouse adapter 220, modem 222, read only memory (ROM) 224,universal serial bus (USB) and other ports 232, and PCI/PCIe devices 234are coupled to South Bridge and I/O controller hub 204 through bus 238.Hard disk drive (HDD) or solid-state drive (SSD) 226 and CD ROM compactdisc read-only memory (CD-ROM) 230 are coupled to South Bridge and I/Ocontroller hub 204 through bus 240. PCI/PCIe devices 234 may include,for example, Ethernet adapters, add-in cards, and PC cards for notebookcomputers. PCI uses a card bus controller, while PCIe does not. ROM 224may be, for example, a flash binary input/output system (BIOS). Harddisk drive 226 and CD-ROM 230 may use, for example, an integrated driveelectronics (IDE), serial advanced technology attachment (SATA)interface, or variants such as external-SATA (eSATA) and micro- SATA(mSATA). A super I/O (SIO) device 236 may be coupled to South Bridge andI/O controller hub (SB/ICH) 204 through bus 238.

Memories, such as main memory 208, ROM 224, or flash memory (not shown),are some examples of computer usable storage devices. Hard disk drive orsolid state drive 226, CD-ROM 230, and other similarly usable devicesare some examples of computer usable storage devices including acomputer usable storage medium.

An operating system runs on processing unit 206. The operating systemcoordinates and provides control of various components within dataprocessing system 200 in FIG. 2. The operating system may be acommercially available operating system for any type of computingplatform, including but not limited to server systems, personalcomputers, and mobile devices. An object oriented or other type ofprogramming system may operate in conjunction with the operating systemand provide calls to the operating system from programs or applicationsexecuting on data processing system 200.

Instructions for the operating system, the object-oriented programmingsystem, and applications or programs, such as application 105 in FIG. 1,are located on storage devices, such as in the form of code 226A on harddisk drive 226, and may be loaded into at least one of one or morememories, such as main memory 208, for execution by processing unit 206.The processes of the illustrative embodiments may be performed byprocessing unit 206 using computer implemented instructions, which maybe located in a memory, such as, for example, main memory 208, read onlymemory 224, or in one or more peripheral devices.

Furthermore, in one case, code 226A may be downloaded over network 201Afrom remote system 201B, where similar code 201C is stored on a storagedevice 201D. in another case, code 226A may be downloaded over network201A to remote system 201B, where downloaded code 201C is stored on astorage device 201D.

The hardware in FIGS. 1-2 may vary depending on the implementation.Other internal hardware or peripheral devices, such as flash memory,equivalent non-volatile memory, or optical disk drives and the like, maybe used in addition to or in place of the hardware depicted in FIGS.1-2. In addition, the processes of the illustrative embodiments may beapplied to a multiprocessor data processing system.

In some illustrative examples, data processing system 200 may be apersonal digital assistant (PDA), which is generally configured withflash memory to provide non-volatile memory for storing operating systemfiles and/or user-generated data. A bus system may comprise one or morebuses, such as a system bus, an I/O bus, and a PCI bus. Of course, thebus system may be implemented using any type of communications fabric orarchitecture that provides for a transfer of data between differentcomponents or devices attached to the fabric or architecture.

A communications unit may include one or more devices used to transmitand receive data, such as a modem or a network adapter. A memory may be,for example, main memory 208 or a cache, such as the cache found inNorth Bridge and memory controller hub 202. A processing unit mayinclude one or more processors or CPUs.

The depicted examples in FIGS. 1-2 and above-described examples are notmeant to imply architectural limitations. For example, data processingsystem 200 also may be a tablet computer, laptop computer, or telephonedevice in addition to taking the form of a mobile or wearable device.

Where a computer or data processing system is described as a virtualmachine, a virtual device, or a virtual component, the virtual machine,virtual device, or the virtual component operates in the manner of dataprocessing system 200 using virtualized manifestation of some or allcomponents depicted in data processing system 200. For example, in avirtual machine, virtual device, or virtual component, processing unit206 is manifested as a virtualized instance of all or some number ofhardware processing units 206 available in a host data processingsystem, main memory 208 is manifested as a virtualized instance of allor some portion of main memory 208 that may be available in the hostdata processing system, and disk 226 is manifested as a virtualizedinstance of all or some portion of disk 226 that may be available in thehost data processing system. The host data processing system in suchcases is represented by data processing system 200.

With reference to FIG. 3, this figure depicts a block diagram of anexample configuration for providing complementary media content forselected media content in accordance with an illustrative embodiment.Client device 110 is an example of client device 110 of FIG. 1 andincludes a processor 302, a memory 304, a user input device 306, adisplay device 308, and a client application 310. Processor 302 isconfigured to retrieve instructions from memory 304 and execute theinstructions to perform various operations of client device 110 asdescribed herein. In one or more embodiments, user input device 306 isconfigured to provide one or more input devices to allow the user tointeract with client device 110. In one or more embodiments, displaydevice 308 is configured to display media content such as complementarymedia content to a user of client device 110. Client application 310includes a graphical user interface (GUI) component 312 to allow a userselection of media content, display complementary media content choicesto the user, receive a user selection of complementary media contentfrom the display choices from the user, and provide the selectedcomplementary media content to the user.

Server 104 is an example of server 104 of FIG. 1 and includes aprocessor 314, a memory 316, an application 105. Processor 314 isconfigured to retrieve instructions from memory 316 and execute theinstructions to perform various operations of server 104 as describedherein. Application 105 includes a content analysis component 318, atopic rating component 320, and a complementary content search enginecomponent 322. Application 105 is configured to perform the operationsassociated with providing complementary media content for selected mediacontent as described herein. Content analysis component 318 isconfigured to receive selected media content and analyze the selectedcontent to extract one or more topics and perspectives from the selectedmedia content as described herein. Topic rating component 320 isconfigured to determine a topic rating of the extracted topics andassociated perspectives including one or more of topic orthogonality,opposition, independence, and diversity. Complementary content searchengine component 322 is configured to search one or more complementarycontent sources 324 based upon the topic rating to determine one or morechoices of complementary media content for the extracted topics andperspectives as described herein.

Complementary content source(s) 324 include one or more sources of mediacontent that are complementary to topics and perspectives determinedfrom media content selected by a user. In particular embodiments, one ormore of complementary content source(s) 324 include content sources suchas document databases, websites, repositories, and other sources ofmedia content.

In one or more embodiments, application 105 is configured to send theone or more choices of complementary media content to client application310 of client device 110. In the embodiment, client application 310displays the choices of complementary media content to a user of clientdevice 110 within a list, and receives a selection of one or more of thecomplementary media content from the user. In the embodiment, clientapplication 310 sends the selection of complementary media content toserver 104, and server 104 retrieves the selected complementary mediacontent from complementary content source(s) 324.

With reference to FIGS. 4A-4B, these figures depict an example of a webbrowser based GUI 400 in accordance with an illustrative embodiment.With reference to FIG. 4A, this figure depicts GUI 400 includingdisplayed content 402 and a button 404. In the illustrated example, auser viewing content 402 selects button 404 to indicate a desire to viewcomplementary media content for content 402. In the example, clientdevice 110 sends the selected content 402 to server 104. Application 105extracts topics and perspectives from select content 402, determines atopic rating from the extracted topics and perspectives, searchescomplementary content source(s) 324 based upon the topic rating toobtain complimentary content search results, and sends the complimentarycontent search results to client device 110. With reference to FIG. 4B,this figure depicts GUI 400 showing complimentary content search results406 in a list form to allow selection of one or more of the searchresults by the user. Upon selection of the one or more search results,client device 110 sends the selected search results to server 104.Application 105 retrieves the complementary media content associatedwith selected search results and provides the complementary mediacontent to client device 110 for display within GUI 400.

With reference to FIG. 5, this figure depicts an example of a calendarapplication based GUI 500 in accordance with an illustrative embodiment.With reference to FIG. 5, this figure depicts GUI 500 including calendarentries and a button 404 associated with one or more of the calendarentries to allow a user to select button 404 to obtain alternativepoints of view on a meeting topic associated with the particular meetingcorresponding to the calendar entry. For example, a user preparing for ameeting on the topic of the future of blockchain applications may pressthe button and become better prepared by being provided withcomplementary content for the topic including alternative points of view(e.g. links to presentations, web pages, articles, etc.). In otherparticular embodiments, the buttons may also be pressed after a meetingto learn more about a meeting topic of a past meeting.

With reference to FIG. 6, this figure depicts a flowchart of an exampleprocess 600 for providing complementary media content for selected mediacontent in accordance with an illustrative embodiment. In 602,application 105 of server 104 receives a content selection from a userof client device 110 of a content presentation in which the contentselection includes media content for which the user desires to receivecomplementary media content. In 604, application 105 extracts one ormore salient topics {T₁, . . . , T_(N)} from the selected media content.In one or more embodiments, the extracted topic is representative of asubject conveyed within the selected content.

In particular embodiments, the extraction of topics from the selectedcontent includes transforming the topics into vector representations ina vector space. In particular embodiments, the topic extraction isperformed by one or more of probabilistic latent semantic indexing(PLSI), Latent Dirichlet allocation (LDA), Pachinko allocation, singularvalue decomposition (SVD), the method of moments, algorithms based uponnon-negative matrix factorization (NMF), or any other known algorithm orprocedure for extracting topics from multimedia content.

In block 606, application 105 extracts one or more perspectivesassociated with each topic from the selected content. In one or moreembodiments, a particular perspective is representative of a point ofview conveyed within the selected content regarding the topic. In aparticular embodiment, application 105 divides up sentences from theselected content containing statements of point of view or asserted factfrom the content are divided up and associates the sentences, to theextent possible, with a particular topic Ti. In particular embodiments,statements that are not strongly associated with any topic determinedfrom the content are discarded. In other particular embodiments, one ormore sentences may be associated with more than one topic. For thosesentences associated with at least one topic, application 105 extractswhat are determined to be statements of opinion and as well asstatements of asserted fact since “statements of fact” may also be amatter of disagreement such as in the political realm. In particularembodiments, detecting of assertions of fact and assertions of opinionare determined using natural language processing (NLP) such as describedin U.S. Pat. No. 9,483,582. In one or more embodiments, the statementsof facts and statements of opinion form one or more perspectives for thetopic conveyed by the selected content.

In 608, application 105 determines a topic rating of the extractedtopics and associated perspectives including a topic diversity ofextracted topics such as one or more of orthogonality, opposition, andindependence, based upon the extracted topics and perspectives. In 610,application 105 provides the topic rating to the user. In a particularembodiment, providing the topic rating to the user includes presentingthe topic rating within a GUI.

In 612, application 105 creates a negation corresponding to eachperspective representing a complementary point of view to the particularperspective. In particular embodiments, a statement of fact or opinion,and the associated negation, are really equivalence classes ofstatements, all of which convey to the same thing. Thus, a key componentis to find the classes in each article and determine, for each class,how numerous the positive assertions are compared with the negativeassertions. If there is a noticeable difference then it can be statedwith some confidence that for topic Ti, the content (e.g., an article)represents the assertion of fact/opinion A_(j).

The collection of all such {A_(j)} for the given topic is somewhatrepresentative of the article's stance on topic T_(i). A second articlewill take on opposing views to the extent that, for each given T_(i), itrepresents {˜A_(j)} for all j where ˜A_(j) denotes “not A_(j)”.

The degree to which another article disagrees with the present articlefor a given topic T_(i) can be established based on how many of theassertions A_(j) from the first article show up in the form ˜A_(j) inthe other article. This provides a simple measure of the degree to whichone article disagrees with another on a given topic. If, on the otherhand, one is looking for the degree of disagreement across all topics,then the disagreement score can either be averaged across topics, or aweighted average of the disagreement scores can be taken, consideringthe degree of importance the given topic is to the article in question.

In 614, application 105 searches one or more complementary media sourcesusing the negations to determine search results identifyingcomplementary media content to the selected media content. In 616,application 105 receives the search results of the complementary mediasources. In 618, application 105 filters the search results based on thetopic rating. In 620, application 105 provides the complementary searchresults to the user 620. In 622, application 105 receives a searchresult selection from the user selection one or more of thecomplementary media sources. In 624, application 105 retrieves theselected complementary media content from the complementary mediacontent source(s). In 626, application 105 provides the complimentarymedia content to the user via the client device. The procedure 600 thenends.

Thus, a computer implemented method, system or apparatus, and computerprogram product are provided in the illustrative embodiments forproviding complementary media content for selected media content andother related features, functions, or operations. Where an embodiment ora portion thereof is described with respect to a type of device, thecomputer implemented method, system or apparatus, the computer programproduct, or a portion thereof, are adapted or configured for use with asuitable and comparable manifestation of that type of device.

Where an embodiment is described as implemented in an application, thedelivery of the application in a Software as a Service (SaaS) model iscontemplated within the scope of the illustrative embodiments. In a SaaSmodel, the capability of the application implementing an embodiment isprovided to a user by executing the application in a cloudinfrastructure. The user can access the application using a variety ofclient devices through a thin client interface such as a web browser(e.g., web-based e-mail), or other light-weight client-applications. Theuser does not manage or control the underlying cloud infrastructureincluding the network, servers, operating systems, or the storage of thecloud infrastructure. In some cases, the user may not even manage orcontrol the capabilities of the SaaS application. In some other cases,the SaaS implementation of the application may permit a possibleexception of limited user-specific application configuration settings.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

What is claimed is:
 1. A method comprising: receiving a selection ofcontent from a content presentation; extracting, using natural languageprocessing (NLP), a plurality of topics from the selected content, thetopics representative of respective subjects conveyed within theselected content; extracting, using NLP, a plurality of perspectivescomprising at least one perspective associated with each topic, theperspectives representative of respective points of view conveyed withinthe selected content regarding the associated topic, the perspectivescomprising respective sentences from the selection of content, whereinthe extracting comprises dividing the content into sentences, discardingsentences not associated with any of the plurality of topics, and, foreach remaining sentence, associating the sentence with one of theplurality of topics and detecting a perspective for the associated topicconveyed by the sentence; determining a topic rating of the extractedtopics and associated perspectives based upon the extracted topics andassociated perspectives, the topic rating representative of a topicdiversity among the extracted topics and associated perspectives,wherein the determining of the topic rating includes measuring the topicdiversity by representing the sentences of the respective perspectivesin vector space as an ensemble of respective vectors and comparing thevectors to each other, the comparing including detecting orthogonalityand independence among pairs of the vectors; presenting the topic ratingwithin a graphical user interface (GUI); creating a negation associatedwith a particular perspective of the plurality of perspectivesassociated with a particular topic of the plurality of topics, thenegation representing an opposing point of view that is complementary tothe particular perspective; searching a content source for complementarycontent based at least in part on the negation to determine acomplementary content search result for the particular perspective;generating a disagreement score representative of an extent to which theselected content disagrees with the complementary content search resultfor the particular topic; and presenting the complementary contentsearch result within the GUI.
 2. The method of claim 1, furthercomprising: detecting a degree of orthogonality between the particularperspective and the complementary content search result.
 3. The methodof claim 2, further comprising: presenting the complementary contentsearch result in the GUI, wherein a color of the complementary contentsearch result is indicative of the degree of orthogonality between theparticular perspective and the complementary content search result. 4.The method of claim 1 wherein the searching of the content source forcomplementary content further comprises searching to determine aplurality of complementary content search results, including saidcomplementary content search result, for the particular perspective;detecting a respective degree of orthogonality between the particularperspective and each of the plurality of complementary content searchresults; presenting the complementary content search results in the GUI,wherein a color of each of the complementary content search results isindicative of the respective detected degree of orthogonality; receivinga selection from among the plurality of complementary content searchresults; retrieving complementary content associated with the selectionfrom among the complementary content search results; and providing thecomplementary content within the GUI.
 5. The method of claim 4, whereinthe complementary content is presented within the GUI as part of a Webbrowser plugin.
 6. The method of claim 4, wherein the complementarycontent is presented as closed caption information within a broadcast.7. The method of claim 1, wherein extracting the at least one topicincludes representing the at least one topic as a vector in a vectorspace.
 8. The method of claim 1, wherein the extracting of the at leastone topic includes using one or more of probabilistic latent semanticindexing (PLSI), Latent Dirichlet allocation (LDA), Pachinko allocation,singular value decomposition (SVD), method of moments, and non-negativematrix factorization (NMF).
 9. The method of claim 1, wherein the GUI isconfigured to allow a user to select the content from the contentpresentation.
 10. The method of claim 1, wherein the extracting of thetopic is performed at one or more of a sentence level of contentorganization and a document level of content organization.
 11. Themethod of claim 2, wherein the GUI includes an electronic calendarapplication having at least one calendar entry, the GUI allowingselection of the at least one calendar entry, and wherein thecomplementary content includes at least one of an alternative point ofview of a meeting topic associated with the calendar entry, a link toone or more other calendar entries providing a complementary viewpoint.12. The method of claim 11, wherein the other calendar entries aresorted in order of degree of complementarity.
 13. A computer usableprogram product comprising one or more computer-readable storage medium,and program instructions stored on at least one of the one or morestorage medium, the stored program instructions comprising: programinstructions to receive a selection of content from a contentpresentation; program instructions to extract, using natural languageprocessing (NLP), a plurality of topics from the selected content, thetopics representative of respective subjects conveyed within theselected content; program instructions to extract, using NLP, aplurality of perspectives comprising at least one perspective associatedwith each topic, the perspectives representative of respective points ofview conveyed within the selected content regarding the associatedtopic, the perspectives comprising respective sentences from theselection of content, wherein the program instructions to extractcomprise instructions to divide the content into sentences, programinstructions to discard sentences not associated with any of theplurality of topics, and, for each remaining sentence, programinstructions to associate the sentence with one of the plurality oftopics and detect a perspective for the associated topic conveyed by thesentence; program instructions to determine a topic rating of theextracted topics and associated perspectives based upon the extractedtopics and associated perspectives, the topic rating representative of atopic diversity among the extracted topics and associated perspectives,wherein the determining of the topic rating includes measuring the topicdiversity by representing the sentences of the respective perspectivesin vector space as an ensemble of respective vectors and comparing thevectors to each other, the comparing including detecting orthogonalityand independence among pairs of the vectors; program instructions topresent the topic rating within a graphical user interface (GUI);program instructions to create a negation associated with a particularperspective of the plurality of perspectives associated with aparticular topic of the plurality of topics, the negation representingan opposing point of view that is complementary to the particularperspective; program instructions to search a content source forcomplementary content based at least in part on the negation todetermine a complementary content search result for the particularperspective; program instructions to generate a disagreement scorerepresentative of an extent to which the selected content disagrees withthe complementary content search result for the particular topic; andprogram instructions to present the complementary content search resultwithin the GUI.
 14. The computer usable program product of claim 13,further comprising: program instructions to search a content source forcomplementary content based upon the topic rating to determine one ormore complementary content search results for the extracted topics andperspectives; and program instructions to receive a selection from amongthe one or more complementary content search results.
 15. The computerusable program product of claim 14, further comprising: programinstructions to retrieve complementary content associated with theselected complementary content search results; and program instructionsto provide the complementary content within the GUI.
 16. A computersystem comprising one or more processors, one or more computer-readablememories, and one or more computer-readable storage medium, and programinstructions stored on at least one of the one or more storage medium,for execution by at least one of the one or more processors via at leastone of the one or more memories, the stored program instructionscomprising: program instructions to receive a selection of content froma content presentation; program instructions to extract, using naturallanguage processing (NLP), at least one topic from the selected content,the at least one topic representative of a subject conveyed within theselected content; program instructions to extract, using NLP, aplurality of perspectives comprising at least one perspective associatedwith each topic, the perspectives representative of respective points ofview conveyed within the selected content regarding the associatedtopic, the perspectives comprising respective sentences from theselection of content, wherein the instructions to extract compriseinstructions to divide the content into sentences, instructions todiscard sentences not associated with any of the plurality of topics,and, for each remaining sentence, instructions to associate the sentencewith one of the plurality of topics and detect a perspective for theassociated topic conveyed by the sentence; program instructions todetermine a topic rating of the extracted topics and associatedperspectives based upon the extracted topics and associatedperspectives, the topic rating representative of a topic diversity amongthe extracted topics and associated perspectives, wherein thedetermining of the topic rating includes measuring the topic diversityby representing the sentences of the respective perspectives in vectorspace as an ensemble of respective vectors and comparing the vectors toeach other, the comparing including detecting orthogonality andindependence among pairs of the vectors; program instructions to presentthe topic rating within a graphical user interface (GUI); programinstructions to create a negation associated with a particularperspective of the plurality of perspectives associated with aparticular topic of the plurality of topics, the negation representingan opposing point of view that is complementary to the particularperspective; program instructions to search a content source forcomplementary content based at least in part on the negation todetermine a complementary content search result for the particularperspective; program instructions to generate a disagreement scorerepresentative of an extent to which the selected content disagrees withthe complementary content search result for the particular topic; andprogram instructions to present the complementary content search resultwithin the GUI.
 17. The method of claim 1, further comprising:determining assertions of opinion associated with the particular topicin the selected content; and determining assertions of fact associatedwith the particular topic in the selected content.
 18. The method ofclaim 17, further comprising: determining opposing assertions of opinionassociated with the particular topic in the complementary content searchresult; and determining opposing assertions of fact associated with theparticular topic in the complementary content search result.
 19. Themethod of claim 18, wherein the disagreement score is based at least inpart on a first total number of assertions associated with theparticular topic in the selected content and a second total number ofopposing assertions associated with the particular topic in thecomplementary content search result.
 20. The method of claim 19, whereinthe first total number of assertions includes the assertions of opinionand the assertions of fact, and wherein the second total number ofopposing assertions includes the opposing assertions of opinion and theopposing assertions of fact.